How to Clean and Normalize Bank Statement CSV Data

After converting a bank statement PDF to CSV, the data often needs cleaning before it can be imported into accounting software. Dates may be in different formats, amounts may include currency symbols, and descriptions may contain unnecessary whitespace.

Common Issues in Bank Statement CSVs

Date Format Inconsistencies Banks use various date formats: MM/DD/YYYY, DD/MM/YYYY, YYYY-MM-DD, or even text like "Jan 15, 2025". Your accounting software likely expects one specific format.

Amount Formatting - Currency symbols mixed with numbers ("$1,234.56") - Parentheses for negative numbers ("(500.00)") - Different decimal separators ("1.234,56" vs "1,234.56")

Description Noise - Extra whitespace and line breaks - Truncated merchant names - Reference numbers mixed with descriptions - ALL CAPS text

Cleaning Steps

1. Standardize Dates Convert all dates to ISO 8601 format (YYYY-MM-DD) or your accounting software's preferred format.

2. Clean Amounts Remove currency symbols, thousands separators, and convert parenthetical negatives to minus signs.

3. Normalize Descriptions Trim whitespace, fix capitalization, and separate reference numbers from merchant names where possible.

4. Add Categories If your accounting software supports categories, consider adding a category column based on common transaction descriptions.

5. Validate Totals Sum all amounts and compare against the statement's reported total. Verify opening and closing balances.

Using letPdf for Clean Output

letPdf handles most cleaning automatically during conversion: - Dates are standardized to YYYY-MM-DD format - Amounts are properly signed and formatted - Descriptions are trimmed and normalized - Output is UTF-8 encoded for universal compatibility

This eliminates most manual cleaning steps and produces files ready for direct import.